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Google just announced that it has been riverline floods, up to seven days in advance in some cases. This isn’t just tech company hyperbole, as the findings were actually published Nature. Floods are the most common natural disaster throughout the world, so any early warning system is good news.
Floods have been notoriously tricky to predict, as most rivers don’t have streamflow gauges. Google got around this problem by with all kinds of relevant data, including historical events, river level readings, elevation and terrain readings and more. After that, the company generated localized maps and ran “hundreds of thousands” of simulations in each location. This combination of techniques allowed the models to accurately predict upcoming floods.
The approach built “highly accurate models for very particular locations”, but Google hopes to use these techniques to eventually solve the problem at global scale. While the company did successfully predict some floods a full seven days in advance, the average came in at around five days. Still, Google’s confident that it has extended the “reliability of currently-available global nowcasts from zero to five days.” It’s also significantly improved forecasting in underrepresented regions, like some parts of Africa and Asia.
All told, this technology allowed Google to provide accurate flood forecasting in 80 countries, with a total population of 460 million. The company made these forecasts available in Google Search, Google Maps, and via Android notifications. This information is also available via the company’s proprietary web app, which .
So what’s next? Google will continue to explore the “potential of machine learning to create better flood forecasting models” and has teamed up with academic researchers to fine tune the AI-driven approach. The company hopes this will eventually result in a “global end-to-end flood forecasting platform.”
This article originally appeared on Engadget at
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Floods have been notoriously tricky to predict, as most rivers don’t have streamflow gauges. Google got around this problem by with all kinds of relevant data, including historical events, river level readings, elevation and terrain readings and more. After that, the company generated localized maps and ran “hundreds of thousands” of simulations in each location. This combination of techniques allowed the models to accurately predict upcoming floods.
The approach built “highly accurate models for very particular locations”, but Google hopes to use these techniques to eventually solve the problem at global scale. While the company did successfully predict some floods a full seven days in advance, the average came in at around five days. Still, Google’s confident that it has extended the “reliability of currently-available global nowcasts from zero to five days.” It’s also significantly improved forecasting in underrepresented regions, like some parts of Africa and Asia.
All told, this technology allowed Google to provide accurate flood forecasting in 80 countries, with a total population of 460 million. The company made these forecasts available in Google Search, Google Maps, and via Android notifications. This information is also available via the company’s proprietary web app, which .
So what’s next? Google will continue to explore the “potential of machine learning to create better flood forecasting models” and has teamed up with academic researchers to fine tune the AI-driven approach. The company hopes this will eventually result in a “global end-to-end flood forecasting platform.”
This article originally appeared on Engadget at
Console Bang News!